Bursting Neurons in the Hippocampal Formation Encode Features of LFP Rhythms

Burst spike patterns are common in regions of the hippocampal formation such as the subiculum and medial entorhinal cortex (MEC). Neurons in these areas are immersed in extracellular electrical potential fluctuations often recorded as the local field potential (LFP). LFP rhythms within different frequency bands are linked to different behavioral states. For example, delta rhythms are often associated with slow-wave sleep, inactivity and anesthesia; whereas theta rhythms are prominent during awake exploratory behavior and REM sleep. Recent evidence suggests that bursting neurons in the hippocampal formation can encode LFP features. We explored this hypothesis using a two-compartment model of a bursting pyramidal neuron driven by time-varying input signals containing spectral peaks at either delta or theta rhythms. The model predicted a neural code in which bursts represented the instantaneous value, phase, slope and amplitude of the driving signal both in their timing and size (spike number). To verify whether this code is employed in vivo, we examined electrophysiological recordings from the subiculum of anesthetized rats and the MEC of a behaving rat containing prevalent delta or theta rhythms, respectively. In both areas, we found bursting cells that encoded information about the instantaneous voltage, phase, slope and/or amplitude of the dominant LFP rhythm with essentially the same neural code as the simulated neurons. A fraction of the cells encoded part of the information in burst size, in agreement with model predictions. These results provide in-vivo evidence that the output of bursting neurons in the mammalian brain is tuned to features of the LFP

Dynamic Control of Network Level Information Processing through Cholinergic Modulation

Acetylcholine (ACh) release is a prominent neurochemical marker of arousal state within the brain. Changes in ACh are associated with changes in neural activity and information processing, though its exact role and the mechanisms through which it acts are unknown. Here I show that the dynamic changes in ACh levels that are associated with arousal state control informational processing functions of networks through its effects on the degree of Spike-Frequency Adaptation (SFA), an activity dependent decrease in excitability, synchronizability, and neuronal resonance displayed by single cells. Using numerical modeling I develop mechanistic explanations for how control of these properties shift network activity from a stable high frequency spiking pattern to a traveling wave of activity. This transition mimics the change in brain dynamics seen between high ACh states, such as waking and Rapid Eye Movement (REM) sleep, and low ACh states such as Non-REM (NREM) sleep. A corresponding, and related, transition in network level memory recall is also occurs as ACh modulates neuronal SFA. When ACh is at its highest levels (waking) all memories are stably recalled, as ACh is decreased (REM) in the model weakly encoded memories destabilize while strong memories remain stable. In levels of ACh that match Slow Wave Sleep (SWS), no encoded memories are stably recalled. This results from a competition between SFA and excitatory input strength and provides a mechanism for neural networks to control the representation of underlying synaptic information. Finally I show that during the low ACh conditions, oscillatory conditions allow for external inputs to be properly stored in and recalled from synaptic weights. Taken together this work demonstrates that dynamic neuromodulation is critical for the regulation of information processing tasks in neural networks. These results suggest that ACh is capable of switching networks between two distinct information processing modes. Rate coding of information is facilitated during high ACh conditions and phase coding of information is facilitated during low ACh conditions. Finally I propose that ACh levels control whether a network is in one of three functional states: (High ACh; Active waking) optimized for encoding of new information or the stable representation of relevant memories, (Mid ACh; resting state or REM) optimized for encoding connections between currently stored memories or searching the catalog of stored memories, and (Low ACh; NREM) optimized for renormalization of synaptic strength and memory consolidation. This work provides a mechanistic insight into the role of dynamic changes in ACh levels for the encoding, consolidation, and maintenance of memories within the brain.PHDNeuroscienceUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147503/1/roachjp_1.pd

Cellular Classes in the Human Brain Revealed In Vivo by Heartbeat-Related Modulation of the Extracellular Action Potential Waveform

Determining cell types is critical for understanding neural circuits but remains elusive in the living human brain. Current approaches discriminate units into putative cell classes using features of the extracellular action potential (EAP); in absence of ground truth data, this remains a problematic procedure. We find that EAPs in deep structures of the brain exhibit robust and systematic variability during the cardiac cycle. These cardiac-related features refine neural classification. We use these features to link bio-realistic models generated from in vitro human whole-cell recordings of morphologically classified neurons to in vivo recordings. We differentiate aspiny inhibitory and spiny excitatory human hippocampal neurons and, in a second stage, demonstrate that cardiac-motion features reveal two types of spiny neurons with distinct intrinsic electrophysiological properties and phase-locking characteristics to endogenous oscillations. This multi-modal approach markedly improves cell classification in humans, offers interpretable cell classes, and is applicable to other brain areas and species

Beta oscillations underlie top-down, feedback control while gamma oscillations reflect bottom-up, feedforward influences

Prefrontal cortex (PFC) is critical to behavioral flexibility and, hence, the top-down control over bottom-up sensory information. The mechanisms underlying this capacity have been hypothesized to involve the propagation of alpha/beta (8-30 Hz) oscillations via feedback connections to sensory regions. In contrast, gamma (30-160 Hz) oscillations are thought to arise as a function of bottom-up, feedforward stimulation. To test the hypothesis that such oscillatory phenomena embody such functional roles, we assessed the performance of nine monkeys on tasks of learning, categorization, and working memory concurrent with recording of local field potentials (LFPs) from PFC. The first set of tasks consisted of two classes of learning: one, explicit and, another, implicit. Explicit learning is a conscious process that demands top-down control, and in these tasks alpha/beta oscillations tracked learning. In contrast, implicit learning is an unconscious process that is automatic (i.e. bottom up), and in this task alpha/beta oscillations did not track learning. We next looked at dot-pattern categorization. In this task, category exemplars were generated by jittering the dot locations of a prototype. By chance, some of these exemplars were similar to the prototype (low distortion), and others were not (high distortion). Behaviorally, the monkeys performed well on both distortion levels. However, alpha/beta band oscillations carried more category information at high distortions, while gamma-band category information was greatest on low distortions. Overall, the greater the need for top-down control (i.e. high distortion), the greater the beta, and the lesser the need (i.e. low distortion), the greater the gamma. Finally, laminar electrodes were used to record from animals trained on working memory tasks. Each laminar probe was lowered so that its set of contacts sampled all cortical layers. During these tasks, gamma oscillations peaked in superficial layers, while alpha/beta peaked in deep layers. Moreover, these deep-layer alpha/beta oscillations entrained superficial alpha/beta, and modulated the amplitude of superficial-layer gamma oscillations. These laminar distinctions are consistent with anatomy: feedback neurons originate in deep layers and feedforward neurons in superficial layers. In summary, alpha/beta oscillations reflect top-down control and feedback connectivity, while gamma oscillations reflect bottom-up processes and feedforward connectivity

Theta oscillations, timing and cholinergic modulation in the rodent hippocampal circuit

The medial temporal lobe (MTL) is crucial for episodic and spatial memory, and shows rhythmicity in the local field potential and neuronal spiking. Gamma oscillations (>40Hz) are mediatepd by local circuitry and interact with slower theta oscillations (6-10 Hz). Both oscillation frequencies are modulated by cholinergic input from the medial septum. Entorhinal grid cells fire when an animal visits particular locations in the environment arranged on the corners of tightly packed, equilateral triangles. Grid cells show phase precession, in which neurons fire at progressively earlier phases relative to theta oscillation as animals move through firing fields. This work focuses on the temporal organization of spiking and network rhythms, and their modulation by septal inputs, which are thought to be involved in MTL function. First, I recorded grid cells as rats explored open spaces and examined precession, previously only characterized on linear tracks, and compared it to predictions from models. I identified precession, including in conjunctive head-direction-by-grid cells and on passes that clipped the edge of the firing field. Secondly, I studied problems of measuring single neuron theta rhythmicity and developed an improved approach. Using the novel approach, I identified diverse modulation of rat medial entorhinal neurons’ rhythmic frequencies by running speed, independent from the modulation of firing rate by speed. Under pharmacological inactivation of the septum, rhythmic tuning was disrupted while rate tuning was enhanced. The approach also showed that available data is insufficient to prove that bat grid cells are arrhythmic due to low firing rates. In the final project, I optogenetically silenced cholinergic septal cells while recording from hippocampal area CA1. I identified changes in theta rhythmic currents and in theta-gamma coupling. This silencing disrupted performance when applied during the encoding phase of a delayed match to position task. These data support hypothetical roles of these rhythms in encoding and retrieval and suggest possible mechanisms for their modulation. Together, evidence from these projects suggests a role for theta in the function of spatial and episodic memory. These oscillations have important implications for communication and computation, and they can provide a substrate for efficient brain function

Bursts of beta oscillations across the brain as a neurophysiological correlate of contextual novelty

The retrosplenial cortex and hippocampus are brain regions which have been shown to be highly involved in contextual memory. In order to discover neurophysiological correlates of contextual memory in these regions, we used in vivo electrophysiology in awake, behaving mice while they explored a series of novel and familiar environments. Additionally, in order to better understand the specific neurophysiological effects of Alzheimer’s disease-associated amyloid pathology on the retrosplenial cortex and hippocampus, we compared network activity between wild-type mice and J20 mice, a transgenic mouse model which develops widespread age-related amyloid pathology and memory impairments. We detected transient bursts of beta oscillations in both the retrosplenial cortex and hippocampus that were synchronous between these regions and upregulated during contextual novelty. Moreover, spiking of neurons in the retrosplenial cortex was significantly increased during beta bursts. In J20 mice, we noted numerous examples of altered network activity, including aberrant beta bursting which is not coupled to neuronal spiking. Through the use of EEG recordings in mice, we demonstrated that beta bursts can be detected across the cortex, and are highly synchronous between different brain regions. Finally, we demonstrated that it is possible to pharmacologically induce beta bursting in the retrosplenial cortex in vitro through the use of carbachol, a muscarinic acetylcholine receptor agonist, providing an assay for better understanding the mechanisms underlying beta bursting. These findings suggest that transient beta bursting across the brain provides brief windows of effective communication between brain regions, which may underlie the formation of cortical representation of contexts, and may be impaired in Alzheimer’s disease

Interactions between anterior thalamus and hippocampus during different behavioral states in the rat by Héctor Penagos.

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 123-132).The anterior thalamus and hippocampus are part of an extended network of brain structures underlying cognitive functions such as episodic memory and spatial navigation. Earlier work in rodents has demonstrated that hippocampal cell ensembles re-express firing profiles associated with previously experienced spatial behavior. Such recapitulation occurs during periods of awake immobility, slow wave sleep (SWS) and rapid eye movement sleep (REM). Despite its close functional and anatomical association with the hippocampus, whether or how activity in the anterior thalamus is related to activity in the hippocampus during behavioral states characterized by hippocampal replay remains unknown. Here, we monitor and compare thalamic and hippocampal activities during epochs in which rats execute a simple alternation task on a circular maze as well as during sleep periods before and after track running. We employ a neural decoding algorithm to interpret spiking activity in terms of spatial correlates during wake and REM. We analyze multi unit activity (MUA) to characterize the organization of thalamic and hippocampal populations during SWS. Consistent with their role in spatial navigation, we show that during active locomotion ensembles of thalamic and hippocampal neurons represent the spatial behavior of the rat in a coordinated fashion. However, during periods of hippocampal awake replay their spatial representations become decoupled. During REM, we demonstrate that thalamic activity replicates broad activity patterns associated with awake behavior and that both hippocampus and anterior thalamus concurrently represent similar ambulatory states. During SWS, we establish that the activities in these two areas alternate between frames of elevated firing and periods of little or no activity. We show that there is a tendency for thalamic depolarized states to start and end ahead of hippocampal activity frames. These results may shed light on how information encoded by thalamic circuits could bias or be incorporated into hippocampal replay phenomena.Ph.D